Kevin R. Mackie

Determination of first-order landfill gas modeling parameters and uncertainties

Using first-order kinetic empirical models to estimate landfill gas (LFG) generation and collection rates is well recognized in the literature. The uncertainty in the estimated LFG generation rates is a major challenge in evaluating performance of LFG collection and LFG to energy facilities. In this investigation, four methods for quantifying first-order LFG generation model parameters, methane generation potential, L(0), and methane generation rate constant, k, were evaluated. It was found that the model is insensitive to the approach taken in quantifying the parameters. However, considering the recognition of using the model in the literature, the optimum method to estimate L(0) and k is to determine L(0) using disposed municipal solid waste composition and laboratory component specific methane potential values. The k value can be selected by model fitting and regression using the first-order model if LFG collection data are available. When such data are not available, k can be selected from technical literature, based on site conditions. For five Florida case-study landfills L(0) varied from 56 to 77 m(3) Mg(-1), and k varied from 0.04 to 0.13 yr(-1) for the traditional landfills and was 0.10 yr(-1) for the wet cell. Model predictions of LFG collection rates were on average lower than actual collection. The uncertainty (coefficient of variation) in modeled LFG generation rates varied from ±11% to ±17% while landfills were open, ±9% to ±18% at the end of waste placement, and ±16% to ±203% 50 years after waste placement ended.

Characterization of two novel saccharolytic, anaerobic thermophiles, Thermoanaerobacterium polysaccharolyticum sp. nov. and Thermoanaerobacterium zeae sp. nov., and emendation of the genus Thermoanaerobacterium

Two anaerobic, thermophilic, Gram-positive, non-spore forming bacteria with an array of polysaccharide-degrading enzymes were isolated from the leachate of a waste pile from a canning factory in Hoopeston, East Central Illinois, USA. The results of 16S rDNA sequence homology indicated that their closest relatives belong to the saccharolytic, thermophilic and anaerobic genera of Thermoanaerobacterium and Thermoanaerobacter. Although, the evolutionary distances between these bacteria and their closest relatives are greater than 11%, there is no defining phenotypic characteristic for the creation of a new genus. It is proposed that these bacteria should be placed in the genus Thermoanaerobacterium, which requires emendment of the genus description with regard to the reduction of thiosulfate to sulfur, because neither isolate is capable of this reduction. Thermoanaerobacterium polysaccharolyticum reduces thiosulfate to sulfide, whereas Thermoanaerobacterium zeae is unable to reduce thiosulfate. The cells of both isolates are rod-shaped and exist as single cells or sometimes in pairs. Cells are motile by means of flagella. Growth occurs between 45 and 72 degrees C, with optimum temperature of 65-68 degrees C at pH 6.8. The pH range for growth is from 4 to 8 at a temperature of 65 degrees C. Both organisms ferment glucose, arabinose, maltose, mannose, rhamnose, sucrose, trehalose, xylose, cellobiose, raffinose, melibiose and melezitose. The major end products of fermentation with glucose are ethanol and CO2, with lesser amounts of acetate, formate, lactate and hydrogen. The DNA G+C contents of Thermoanaerobacterium polysaccharolyticum sp. nov. and Thermoanaerobacterium zeae sp. nov. are 46 and 42 mol%, respectively. The type strains are KMTHCJT (= ATCC BAA-17T = DSM 13641T) and mel2T (= ATCC BAA-16T = DSM 13642T), respectively.

Ultra-High-Performance Concrete Bridge Deck Reinforced with High-Strength Steel

Open-grid steel bridge decks are lightweight, but present noise, fatigue damage, ride comfort and maintenance challenges. A lightweight bridge deck system with a solid riding surface could eliminate these problems. Ultra-high-performance concrete (UHPC) shows promise as a material for a new lightweight bridge deck system. This paper describes the development of a low-profile UHPC deck system that addresses the concerns with open-grid steel decks, satisfies strength and serviceability requirements, and meets the strict self-weight requirements for movable bridges. The experimental study shows that the proposed system has great potential to serve as an alternative to open-grid steel decks. The ultimate load capacity of all specimens exceeded the target load for the bridge deck. Although shear was the governing mode of failure in most of the specimens, it was not as abrupt and catastrophic as the commonly seen shear failure mode. The use of standard 180-degree hooks on both ends of the flexural reinforcement helped avoid bond failure. Further research is needed before field implementation of the proposed deck system.

Using a reliability process to reduce uncertainty in predicting crashes at unsignalized intersections

The negative binomial (NB) model has been used extensively by traffic safety analysts as a crash prediction model, because it can accommodate the over-dispersion criterion usually exhibited in crash count data. However, the NB model is still a probabilistic model that may benefit from updating the parameters of the covariates to better predict crash frequencies at intersections. The objective of this paper is to examine the effect of updating the parameters of the covariates in the fitted NB model using a Bayesian updating reliability method to more accurately predict crash frequencies at 3-legged and 4-legged unsignalized intersections. For this purpose, data from 433 unsignalized intersections in Orange County, Florida were collected and used in the analysis. Four Bayesian-structure models were examined: (1) a non-informative prior with a log-gamma likelihood function, (2) a non-informative prior with an NB likelihood function, (3) an informative prior with an NB likelihood function, and (4) an informative prior with a log-gamma likelihood function. Standard measures of model effectiveness, such as the Akaike information criterion (AIC), mean absolute deviance (MAD), mean square prediction error (MSPE) and overall prediction accuracy, were used to compare the NB and Bayesian model predictions. Considering only the best estimates of the model parameters (ignoring uncertainty), both the NB and Bayesian models yielded favorable results. However, when considering the standard errors for the fitted parameters as a surrogate measure for measuring uncertainty, the Bayesian methods yielded more promising results. The full Bayesian updating framework using the log-gamma likelihood function for updating parameter estimates of the NB probabilistic models resulted in the least standard error values.

Landfill gas emission prediction using Voronoi diagrams and importance sampling

Municipal solid waste (MSW) landfills are among the nations largest emitters of methane, a key greenhouse gas, and there is considerable interest in quantifying the surficial methane emissions from landfills. There are limitations in obtaining accurate emissions data by field measurements, and in characterizing an entire landfill with only a few such emissions measurements. This paper proposes an emissions prediction approach using numerous ambient air volatile organic compound (VOC) measurements above the surface of a landfill that are more easily obtained. Many large landfills are already collecting ambient air methane data based on existing regulations. The proposed method is based on the inverse solution of the standard Gaussian dispersion equations. However, only the VOC concentrations and locations are required. The locations of maximum likelihood of the point sources are predicted using Voronoi diagrams, and importance sampling is performed to further refine the locations. Point source strengths are calculated using non-negative least squares, and the point emission rates are then summed to give the total landfill emission rate. The proposed method is successfully demonstrated on a series of four landfill case studies. Three hypothetical landfills were selected for validation studies by forward and backward solution of the dispersion equations. The fourth case study is an active central Florida MSW landfill. The proposed method shows promise in accurately and robustly predicting landfill gas emissions, and requires only measured ambient VOC concentrations and locations.

Response Sensitivity of Highway Bridges to Randomly Oriented Multi-Component Earthquake Excitation

In two-dimensional and single axis three-dimensional finite element analyses, the ground motion incidence angle can play a significant role in structural response. The effect of incidence angle for three-dimensional excitation and response is investigated in this paper for response of highway bridges. Single-degree-of-freedom elastic and inelastic mean spectra were computed from various orientation techniques and found indistinguishable for combinations of orthogonal horizontal components. Probabilistic seismic demand models were generated for the nonlinear response of five different bridge models. The negligible effect of incidence angle on mean ensemble response was confirmed with a stochastic representation of the ground motions.

Comparison of Incremental Dynamic, Cloud, and Stripe Methods for Computing Probabilistic Seismic Demand Models

Probabilistic seismic demand models (PSDMs) are mathematical relations between measures of earthquake intensity and measures of structural response. The models include best estimates as well as considerations of uncertainty. Three methods for obtaining the demand models are compared in this paper: cloud, incremental dynamic, and stripe. A PSDM is derived using each method for a sample reinforced concrete bridge using a single IM (first-mode spectral acceleration) and EDP (column drift ratio). Merits and drawbacks of each method are discussed. For the structure considered, cloud and incremental dynamic analyses yield interchangeable PSDMs for the same amount of computational effort. Stripe analysis should be used only for individual intensity levels, not as a means of generating complete PSDMs.

A Robust Method for Estimating Landfill Methane Emissions

Abstract Because municipal solid waste (MSW) landfills emit significant amounts of methane, a potent greenhouse gas, there is considerable interest in quantifying surficial methane emissions from landfills. The authors present a method to estimate methane emissions, using ambient air volatile organic compound (VOC) measurements taken above the surface of the landfill. Using a hand-held monitor, hundreds of VOC concentrations can be taken easily in a day, and simple meteorological data can be recorded at the same time. The standard Gaussian dispersion equations are inverted and solved by matrix methods to determine the methane emission rates at hundreds of point locations throughout a MSW landfill. These point emission rates are then summed to give the total landfill emission rate. This method is tested on a central Florida MSW landfill using data from 3 different days, taken 6 and 12 months apart. A sensitivity study is conducted, and the emission estimates are most sensitive to the input meteorological parameters of wind speed and stability class. Because of the many measurements that are used, the results are robust. When the emission estimates were used as inputs into a dispersion model, a reasonable scatterplot fit of the individual concentration measurement data resulted.

Development Length of High-Strength Steel Rebar in Ultrahigh Performance Concrete

AbstractUltrahigh performance concrete (UHPC) is increasingly making its way into the construction field. Characterization of UHPC has therefore received much-needed attention in the research arena. One effective application of UHPC is in combination with high-strength steel (HSS) reinforcing rebar in shallow beams or slabs. However, bond and development characteristics of HSS rebar in UHPC have not yet been investigated. This paper presents the experimental results of the pullout and flexure tests conducted with HSS rebar in UHPC. This work was a part of a larger project to develop a new light-weight UHPC-HSS bridge deck system for a moveable bridge. Because the bridge deck was designed with #10 and #22 rebar as the main reinforcement, only these two rebar sizes were used in the experiments. First, pullout specimens were tested with three different embedment lengths of 8, 10, and 12 times the rebar diameter. Then, from the results of pullout specimens, beam specimens were tested with embedment lengths of...

Experimental Evaluation of Aluminum Bridge Deck System

Most of the movable bridges in the United States have open grid steel decks, primarily because they are factory assembled, lightweight, and easy to install. Open grid steel decks, however, are not as skid resistant as solid decks. Costly maintenance, high noise levels, poor riding comfort, and susceptibility to vibrations are among the other disadvantages of these decks. The objective of the research presented in this paper is to evaluate an alternative lightweight extruded aluminum deck system that has a solid surface and meets the loading requirements as well as weight and thickness limits for movable bridge decks. These aluminum deck panels with their tongue and groove connections have previously been used in Europe, mainly in Sweden. A detailed experimental evaluation of the aluminum deck system has been carried out, including static and fatigue load testing on the deck panels, as well as ancillary tests on the connections with the girders. On the basis of the in-depth experimental evaluation and the ...